Triple
T31201303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harriet Wheelwright |
E795481
|
entity |
| Predicate | appearsInLiteraryWorkSetIn |
P46498
|
FINISHED |
| Object | New Hampshire |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: New Hampshire | Statement: [Harriet Wheelwright, appearsInLiteraryWorkSetIn, New Hampshire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appearsInLiteraryWorkSetIn Context triple: [Harriet Wheelwright, appearsInLiteraryWorkSetIn, New Hampshire]
-
A.
appearsInWrittenBy
Indicates that an entity (such as a character, concept, or element) appears in a written work that is authored by a specified creator.
-
B.
literaryWorkInStory
Indicates that one literary work is referenced, featured, or embedded within the narrative of another story.
-
C.
appearsIn
Indicates that an entity is present, featured, or occurs within a particular context, work, or medium.
-
D.
literaryWorkSetInRegion
chosen
Indicates that a literary work’s narrative or events primarily take place within a specified geographic region.
-
E.
authorOfWorkHeAppearsIn
Indicates that a person is the author of a work in which he himself appears as a character or subject.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f224d8c6608190b7882466521f62be |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fcab6e888881908ca9e18660928a40 |
completed | May 7, 2026, 3:10 p.m. |
| PD | Predicate disambiguation | batch_69fc4562a5b88190bad48f083a6dcdfa |
completed | May 7, 2026, 7:55 a.m. |
Created at: April 29, 2026, 9:09 p.m.